Events

PhD Defense Informed Collective Decision-Making via Voting
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Speaker: Qishen Han

Bio

Location : CoRE 301

Committee: 

Professor Lirong Xia

Professor David Pennock

Professor Kangning Wang

Professor Bo Waggoner (external)

Event Type: PhD Defense

Abstract: When groups must make decisions, voting provides a procedurally fair method to aggregate preferences and knowledge. In our polarized, AI-integrated world plagued by misinformation and echo chambers, making fair, informed, and incentive-aware decisions has become both more critical and more challenging. The challenge grows as AI systems increasingly participate in group decisions, online deliberation platforms, and decentralized autonomous organizations scale democratic participation, and algorithmic filter bubbles fragment our information environment.In real voting scenarios, the preferences of agents are shaped by their social backgrounds as well as their information through different networks. The incomplete information creates a tension between the preferences agents perceive themselves to have and those they would hold under complete information. Similar challenges arise in political elections, corporate board decisions, expert panels, and human-AI collaborationacross domains. Motivated by such scenarios, we would like to ask: How can we make informed, efficient, fair, and incentive-aware collective decisions?This problem sits at a gap between two theoretical traditions. Classical social choice theory offers a rich arsenal of axioms for fair and efficient aggregation, but presupposes agents have well-defined, complete preferences. Epistemic social choice and the Condorcet jury Theorem~\cite{condorcet1785} provide guarantees for information aggregation, but assume agents share common interests and cannot extend to strategic agents. The combination of preference heterogeneity and epistemic uncertainty under strategic behavior introduces complications that existing theory cannot accommodate.My research develops a unified game-theoretic framework that bridges social choice theory and information economics to address this challenge. The foundation is a combined utility model that formally decomposes preferences into subjective components (dependent on social groups) and objective components (dependent on uncertain ground truth), providing the mathematical structure to analyze this rich decision environment. Building on this, I introduce the informed-X desiderata---a benchmark requiring that outcomes match what agents would choose under complete information. Finally, through game-theoretic analysis of strategic behavior, I establish that strategic voting can actually \textit{help} rather than hinder informed decisions, and characterize precisely when this occurs.

Organization: 

Contact  Professor Lirong Xia

Zoom Link: https://rutgers.zoom.us/j/5738638329?pwd=WjZzZjNTWFVkZTBIN1ROcUxvYXpyZz09